Deep learning technologies, due to their advanced pattern extraction and recognition of high-dimensional data, have been widely adopted into multisensor-based fire detection systems.Since deep learning approaches can generate erroneous predictions due to incomplete training datasets, a retraining process over unseen observations is needed.However,
Batteries offer a combination of balancing and regulation services within a smart grid to improve its resilience and flexibility.Maintaining an acceptable state of health and the highest rate of return requires dynamic modelling of the asset and rigorous optimisation.The authors compare the technical cost and economic benefit of battery employment
Abstract There are many extensions of the Standard Model with a dark matter (DM) candidate obtained via the freeze-out mechanism.It can happen that after all experimental and theoretical constraints are taken into account, all parameter points have a relic density below the experimentally measured value.This means that the models solve only partial